activity
20172024
most citedLiDAR-Camera Calibration using 3D-3D Point correspondences

148 citations · 148 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2024

EdgeGaussians -- 3D Edge Mapping via Gaussian Splatting

Kunal Chelani, Assia Benbihi, Torsten Sattler +1

With their meaningful geometry and their omnipresence in the 3D world, edges are extremely useful primitives in computer vision. 3D edges comprise of lines and curves, and methods…

cs.CV2024

Obfuscation Based Privacy Preserving Representations are Recoverable Using Neighborhood Information

Kunal Chelani, Assia Benbihi, Fredrik Kahl +2

Rapid growth in the popularity of AR/VR/MR applications and cloud-based visual localization systems has given rise to an increased focus on the privacy of user content in the local…

cs.CV2023

Privacy-Preserving Representations are not Enough -- Recovering Scene Content from Camera Poses

Kunal Chelani, Torsten Sattler, Fredrik Kahl +1

Visual localization is the task of estimating the camera pose from which a given image was taken and is central to several 3D computer vision applications. With the rapid growth in…

cs.CV2021

How Privacy-Preserving are Line Clouds? Recovering Scene Details from 3D Lines

Kunal Chelani, Fredrik Kahl, Torsten Sattler

Visual localization is the problem of estimating the camera pose of a given image with respect to a known scene. Visual localization algorithms are a fundamental building block in…

cs.RO2017★ 148 cited

LiDAR-Camera Calibration using 3D-3D Point correspondences

Ankit Dhall, Kunal Chelani, Vishnu Radhakrishnan +1

With the advent of autonomous vehicles, LiDAR and cameras have become an indispensable combination of sensors. They both provide rich and complementary data which can be used by va…